Make sure that secrets would work on aws

.env.template

@@ -1,7 +1,7 @@
 OPENAI_API_KEY=sk
 WEAVIATE_URL =
 WEAVIATE_API_KEY =
-ENVIRONMENT = docker
+ENV = docker
 POSTGRES_USER = bla
 POSTGRES_PASSWORD = bla
 POSTGRES_DB = bubu

cognitive_architecture/config.py

@@ -31,12 +31,29 @@ class Config:
     embedding_chunk_size: int = 300
 
     # Database parameters
-    graph_database_url: str = os.getenv('GRAPH_DB_URL')
+    if os.getenv('ENV') == 'prod' or os.getenv('ENV') == 'dev' or os.getenv('AWS_ENV') == 'dev' or   os.getenv('AWS_ENV') == 'prd':
-    graph_database_username: str = os.getenv('GRAPH_DB_USER')
+        graph_database_url: str = os.getenv('GRAPH_DB_URL_PROD')
-    graph_database_password: str = os.getenv('GRAPH_DB_PW')
+        graph_database_username: str = os.getenv('GRAPH_DB_USER')
+        graph_database_password: str = os.getenv('GRAPH_DB_PW_PROD')
+    else:
+        graph_database_url: str = os.getenv('GRAPH_DB_URL')
+        graph_database_username: str = os.getenv('GRAPH_DB_USER')
+        graph_database_password: str = os.getenv('GRAPH_DB_PW')
     weaviate_url: str = os.getenv('WEAVIATE_URL')
     weaviate_api_key: str = os.getenv('WEAVIATE_API_KEY')
 
+    postgres_user: str = os.getenv('POSTGRES_USER')
+    postgres_password: str = os.getenv('POSTGRES_PASSWORD')
+    postgres_db: str = os.getenv('POSTGRES_DB')
+    if os.getenv('ENV') == 'prod' or os.getenv('ENV') == 'dev' or os.getenv('AWS_ENV') == 'dev' or os.getenv('AWS_ENV') == 'prd':
+        postgres_host: str = os.getenv('POSTGRES_PROD_HOST')
+    elif os.getenv('ENV') == 'docker':
+        postgres_host: str = os.getenv('POSTGRES_HOST_DOCKER')
+    elif os.getenv('ENV') == 'local':
+        postgres_host: str = os.getenv('POSTGRES_HOST_LOCAL')
+
+
+
 
 
     # Client ID

cognitive_architecture/database/create_database.py

@@ -9,6 +9,10 @@ from postgres.models import operation
 from postgres.models import sessions
 from postgres.models import user
 from postgres.models import docs
+from cognitive_architecture.config import Config
+config = Config()
+config.load()
+
 
 
 from postgres.database import Base
@@ -54,18 +58,15 @@ def create_tables(engine):
     Base.metadata.create_all(bind=engine)
 
 if __name__ == "__main__":
-    username = os.getenv('POSTGRES_USER')
+    #
-    password = os.getenv('POSTGRES_PASSWORD')
+    # username = os.getenv('POSTGRES_USER')
-    database_name = os.getenv('POSTGRES_DB')
+    # password = os.getenv('POSTGRES_PASSWORD')
-    environment = os.environ.get("ENVIRONMENT")
+    # database_name = os.getenv('POSTGRES_DB')
-
+    # environment = os.environ.get("ENV")
-    if environment == "local":
+    host  = config.postgres_host
-        host = os.getenv('POSTGRES_HOST')
+    username = config.postgres_user
-
+    password = config.postgres_password
-    elif environment == "docker":
+    database_name = config.postgres_db
-        host = os.getenv('POSTGRES_HOST_DOCKER')
-    else:
-        host = os.getenv('POSTGRES_HOST_DOCKER')
 
     engine = create_admin_engine(username, password, host, database_name)
 

cognitive_architecture/database/postgres/database.py

@@ -15,26 +15,23 @@ load_dotenv()
 # # Get the parent directory of your script and add it to sys.path
 # parent_dir = os.path.dirname(script_dir)
 # sys.path.append(parent_dir)
+from cognitive_architecture.config import Config
+config = Config()
+config.load()
 
 
 # in seconds
 MAX_RETRIES = 3
 RETRY_DELAY = 5
 
-username = os.getenv('POSTGRES_USER')
-password = os.getenv('POSTGRES_PASSWORD')
-database_name = os.getenv('POSTGRES_DB')
-import os
 
-environment = os.environ.get("ENVIRONMENT")
 
-if environment == "local":
+host = config.postgres_host
-    host= os.getenv('POSTGRES_HOST')
+username = config.postgres_user
+password = config.postgres_password
+database_name = config.postgres_db
+
 
-elif environment == "docker":
-    host= os.getenv('POSTGRES_HOST_DOCKER')
-else:
-    host= os.getenv('POSTGRES_HOST_DOCKER')
 
 
 

cognitive_architecture/database/vectordb/vectordb.py

@@ -169,7 +169,7 @@ class WeaviateVectorDB(VectorDB):
         else:
             chunk_count = 0
             from cognitive_architecture.database.vectordb.chunkers.chunkers import chunk_data
-            documents = [chunk_data(chunk_strategy="VANILLA", source_data=observation, chunk_size=50,
+            documents = [chunk_data(chunk_strategy="VANILLA", source_data=observation, chunk_size=300,
                        chunk_overlap=20)]
             for doc in documents[0]:
                 chunk_count += 1

entrypoint.sh

@@ -1,5 +1,6 @@
 #!/bin/bash
 export ENVIRONMENT
+export ENV
 # Run Python scripts with error handling
 echo "Running fetch_secret.py"
 python cognitive_architecture/fetch_secret.py

main.py

@@ -320,7 +320,7 @@ async def user_context_enrichment(session, user_id:str, query:str)->str:
     final_result = generate_graph(entire_context)
     logging.info("Final result is %s", final_result)
 
-    return final_result
+    return final_result.response